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Andreas StadlbauerView profile

Adjunct Professor

• Biomedical Imaging
• Medical Physics
• Artificial Intelligence in Medicine
• +7 more

Prof. Dr. Andreas Stadlbauer is a medical physicist affiliated with the Clinical Institute for Diagnostic and Interventional Radiology at St. Pölten University Hospital and the Department of Neurosurgery at Friedrich-Alexander University Erlangen-Nuremberg. He holds an adjunct professorship at the University of Erlangen-Nuremberg and contributes to both clinical and academic research in biomedical imaging and AI applications in oncology. University: Friedrich-Alexander University Erlangen-Nuremberg Hospital Affiliation: St. Pölten University Hospital Department: Department of Neurosurgery Academic Rank: Adjunct Professor His research focuses on advanced MRI techniques, particularly physio-metabolic imaging of brain tumors, oxygen metabolism, and the integration of artificial intelligence in clinical diagnostics. He has led research on glioma classification, tumor microenvironment characterization, and deep learning models for radiomic analysis. The recent publications highlight a strong trend toward AI-driven diagnostic tools in neuro-oncology, particularly in differentiating glioblastomas from metastases and predicting genetic mutations using machine learning. His work emphasizes the clinical translation of complex imaging data into actionable insights. Artificial Intelligence in Oncology Medical Imaging and Radiomics Brain Tumor Metabolism Deep Learning for MRI Analysis Oxygen Metabolism Imaging Clinical Decision Support Systems Prof. Stadlbauer has been involved in seed-funded research projects developing deep learning algorithms for clinical integration. He collaborates extensively with neurosurgeons, radiologists, and oncologists across institutions, contributing to multidisciplinary tumor boards and translational research initiatives. He completed his doctorate in medical physics in 2004, habilitation in 2008, and an MBA in Health Management in 2010. His academic journey reflects a blend of technical expertise and leadership in healthcare innovation.

• Global Oncology
• Prostate Cancer
• Bladder and Kidney Cancer
• +7 more

Priti Lal, MD, is an Associate Professor in the Department of Pathology and Laboratory Medicine at the University of Pennsylvania's Perelman School of Medicine. She serves as the Director of GU Pathology and is an Associate Scholar at the Center for Global Health. Her work bridges advanced pathology, AI-driven diagnostics, and global oncology, with a strong focus on improving cancer outcomes for men of African descent. Her research interests lie at the intersection of global oncology , medical education , and digital pathology . She specializes in bladder, kidney, and prostate cancers, applying cutting-edge computational image analysis to develop nondestructive, AI-based prognostic tools such as Histotyping and AAstro . These innovations aim to address disparities in prostate cancer outcomes by creating population-specific models for African American and African men. The recent publications highlight a strong trend in leveraging AI and genomics to uncover biologically distinct cancer pathways and improve risk stratification. Her work emphasizes stromal morphology and gland structure in prognostication, moving beyond traditional clinical parameters to enhance accuracy. Scientific recognition includes: Co-inventor of US Patent US20210035694A1 for an AI-derived stromal signature in prostate cancer Dr. Lal is deeply involved in global health mentorship, particularly through the MADCAP consortium—a collaborative network involving Harvard, Moffit, Penn, and ten African countries. She mentors students and trainees from Africa, promoting capacity building in molecular diagnostics and pathology education. While specific grant details are not listed, her leadership in international research initiatives suggests active grant-supported work. She leads pathology innovation at Penn and is a key figure in the MADCAP consortium, driving collaborative research and education across continents. Her lab focuses on translating AI-based image analysis into clinical tools for equitable cancer care.

• Network Science
• Machine Learning
• Theoretical Computer Science
• +5 more

Jennifer Chayes is Dean of the College of Computing, Data Science, and Society and a Professor at the University of California, Berkeley, with appointments in Electrical Engineering and Computer Sciences, Mathematics, Statistics, and Information. She co-founded Microsoft Research New England, New York City, and Montreal, leading interdisciplinary research for 23 years before joining Berkeley in 2020. Previously, she was a Professor of Mathematics at UCLA, where she received the Distinguished Teaching Award. Education PhD in Mathematical Physics (1983), Princeton University BA in Biology and Physics (1979), Wesleyan University Her research spans network science , machine learning , and theoretical computer science , focusing on phase transitions in networks, graphons for large-scale network modeling, and applications in cancer immunotherapy , ethical AI , and climate change . Her work on graph limits and exchangeable graphs has foundational implications for network analysis. Recent publications highlight trends in sparse graph theory , privacy-preserving algorithms , and fairness in AI . Awards include the Anita Borg Institute Women of Vision Leadership Award (2012), SIAM John von Neumann Lecture Prize (2015), and ACM Distinguished Service Award (2020). She is a member of the National Academy of Sciences and a Fellow of multiple academic societies. Chayes actively promotes Diversity in STEM and serves on advisory boards for institutions like MIT’s Schwarzman College of Computing, the Howard Hughes Medical Institute, and the National Science Foundation’s Institute for AI and Fundamental Interactions.

Catia PesquitaView profile

Associate Professor

• Semantic Web
• Biomedical Ontologies
• Knowledge Graphs
• +7 more

Catia Pesquita is an Associate Professor in Computer Science at the Faculty of Sciences of the University of Lisbon , where she is also a Senior Researcher at LASIGE and leads the Health and Biomedical Informatics Research Line . With a multidisciplinary background in Biology and Computer Science, she focuses on Artificial Intelligence and Data Science applications in life and health sciences . Her research spans Semantic Web , Biomedical Ontologies , Knowledge Graphs , and Explainable AI , with significant contributions to ontology matching and semantic similarity . Education: PhD in Computer Science - Bioinformatics (2012) MSc in Bioinformatics (2008) Degree in Cell Biology and Biotechnology (2005) Current Projects: KATY (2021-2024): AI-Empowered Personalized Medicine for cancer treatments. BRAINTEASER (2021-2024): AI for ALS and MS disease progression models. Research Outputs: Developed tools like AgreementMakerLight (AML) , KGsim-benchmark , and the Epidemiology Ontology . Over 133 publications with significant citations (32,909 reads, 3,889 citations). Teaching: Lectures advanced topics in Databases , Data Integration , Bioinformatics , and Big Data . Advocacy: Vice-president of Biodata.pt , promoting biological data valorization in Portugal. Actively involved in initiatives to promote computer science careers to young women .

• Mitochondrial Biology
• Aging Research
• Genomic Instability
• +3 more

Sharath Anugula serves as a Guest Researcher in the Department of Cellular and Molecular Medicine at the University of Copenhagen's Faculty of Health and Medical Sciences, specifically within the Molecular Aging Program and Juel-Rasmussen Group. His research is centered at Panum Instituttet in Copenhagen. Dr. Anugula's research interests focus on the intricate relationship between mitochondrial function, genomic stability, and aging processes. His work bridges molecular biology, genetics, and systems approaches to understand fundamental mechanisms of biological aging. He has made significant contributions to understanding how DNA repair mechanisms, particularly REV1-mediated processes, interact with mitochondrial metabolism in aging contexts. His publication record demonstrates expertise in mitochondrial biology, with research examining how metabolic shifts, genomic instability, and nucleotide synthesis pathways influence aging trajectories and disease development. His work often employs both experimental and computational approaches to model complex biological systems. Anugula completed his Ph.D. at the University of Copenhagen in 2021 with research focused on nucleus-mitochondria communication in healthy aging. His scholarly output includes journal articles in Heliyon, Mitochondrion, and Experimental Gerontology, as well as book chapters on aging biology. His collaborative research network includes prominent scientists in aging research, particularly Professor Lene Juel Rasmussen, with whom he has published multiple studies examining the molecular underpinnings of aging processes.

Xia NingView profile

Professor

• Artificial Intelligence
• Machine Learning
• Data Mining
• +7 more

Xia Ning is a Professor jointly appointed in the Department of Computer Science and Engineering , the Division of Medicinal Chemistry and Pharmacognosy (College of Pharmacy), and the Department of Biomedical Informatics at The Ohio State University . She also holds affiliation with the Translational Data Analytics Institute at OSU. Education: Ph.D. in Computer Science & Engineering, University of Minnesota, Twin Cities (2012) M.S. in Computer Science, University of Minnesota, Twin Cities M.S. in Statistics, University of Minnesota, Twin Cities B.S. in Computer Science, Chu Kechen Honors College, Zhejiang University, China Research Focus : The Ning Lab pioneers data-driven Artificial Intelligence, Machine Learning, and Big-Data analytics with targeted applications in drug discovery, medical informatics, health informatics, and e-commerce . Recent thrusts include generative AI for molecule design, graph neural networks for retrosynthesis, large-language models specialized for chemistry (LlaSMol) and e-commerce (eCeLLM), and reinforcement-learning frameworks for precision-medicine drug selection. The lab’s methodologies are intentionally generalizable, enabling spill-over benefits to domains such as social networks and system monitoring. Publication Trends : Over the past four years Professor Ning has released a steady stream of high-impact articles spanning retrosynthesis planning, LLM instruction tuning for scientific domains, reinforcement learning for drug discovery, and COVID-19 health-analytics . These works repeatedly integrate cutting-edge AI techniques (deep RL, graph Transformers, large-scale instruction datasets) with rigorous experimental validation in chemistry and biomedicine. Scientific Awards & Honors : Sanofi iDEA-TECH Award (2024) 10-Year Highest-Impact Award, International Conference on Data Mining (ICDM, 2020) Grants & Collaborations : Funding includes the Sanofi iDEA-TECH Award and collaborative grants with Amazon Web Services for COVID-19 knowledge graphs. Her open-source datasets (ECInstruct, SMolInstruct, CTKG) and models (G2Retro, LlaSMol, eCeLLM) are publicly released on HuggingFace and GitHub, fostering broad academic and industrial adoption. Labs & Teams : Professor Ning heads the Ning Lab at OSU, a multidisciplinary team focusing on AI/ML methodology and translational applications in health and medicine. The lab actively releases code and interactive web portals to accompany each major publication.

• Substance Use Epidemiology
• Psychiatric Epidemiology
• Opioid Policy Analysis
• +4 more

Silvia S. Martins, MD, PhD, is Professor of Epidemiology at Columbia University Mailman School of Public Health, where she directs the Substance Use Epidemiology Unit and co-directs the NIDA T32 Substance Abuse Epidemiology Training Program. She serves as Vice Dean for Faculty and holds affiliations with Columbia's Global Health Initiative, Injury Science Center, and Population Research Center. Her education includes an MD from UFPR-Brazil (1998) and a PhD from the University of São Paulo (2003). Dr. Martins' research examines substance use epidemiology through interdisciplinary lenses, focusing on: Policy impacts of cannabis/opioid regulations on overdose rates and usage patterns Machine learning applications for analyzing drug policy effectiveness Child/adolescent psychiatric epidemiology and global substance use disparities Urban health interventions and community-based substance abuse prevention Her work spans national contexts including the U.S., Brazil, and Uruguay. Her publications demonstrate strong thematic coherence, with recent work emphasizing: Quantitative analysis of cannabis/opioid policy impacts using longitudinal data Innovative methods (e.g., machine learning, geospatial modeling) in epidemiological research Health equity dimensions of substance policies across racial/ethnic groups Maternal health and polysubstance use during public health crises Awards & Honors: Tow Leadership Scholar (2021-2023) Columbia University Irving Medical Center Mentor of the Year (2021) Calderone Health Equity Award (2021) National Hispanic Science Network Mentoring Award (2021) Dean's Award for Excellence in Mentoring (2017) Joseph Ciarrocchi Award for Youth Gambling Research (2011) As principal investigator on multiple NIH grants since 2006, she leads projects examining: Synergistic effects of opioid/cannabis policies in the U.S. Drug overdose trends in Latin America (Brazil, Colombia, Mexico) Unemployment insurance effects on drug outcomes during COVID-19 She mentors early-career researchers through the NIDA T32 program, with >90 mentee-led publications. She directs the Substance Use Epidemiology Unit and co-leads the PHIOS interdisciplinary group. Additional affiliations include Columbia’s Center for Injury Science and Prevention, Institute of Latin American Studies, and Global Mental Health Program.

• Systems Biology
• Stress Response
• Stem Cell Differentiation
• +3 more

Ala Trusina is an Associate Professor at the Niels Bohr Institute , University of Copenhagen , specializing in Biocomplexity and Biophysics . Her research integrates coarse-grained modeling to study complex biological systems. Key Research Areas Stress Response Systems (diabetes, aging, cancer, inflammation) Stem Cell Differentiation (cell fate coordination, reversibility of states) Complex Systems (species coexistence, epidemics, CRISPR-phage interactions) Methodologies Theoretical: Agent-based modeling, in-silico simulations Experimental: Quantitative single-cell imaging, RNA/protein profiling Collaborations Joshua Brickman (ES cells), Anne Grapin-Botton (pancreas), Feroz Papa (diabetes), Else Kai Hoffman (p53 dynamics) Thomas Mandrup-Poulsen (inflammation), Savas Tay (spatio-temporal regulation) Teaching Physics of Molecular Diseases Numerical Methods in Physics

Hua HeView profile

Professor

• Mixture population modeling
• Causal inference
• Longitudinal data analysis
• +5 more

Hua He is a Professor in the Department of Biostatistics and Data Science at Tulane University's School of Public Health and Tropical Medicine, specializing in advanced statistical methodologies for public health research. Her work bridges theoretical biostatistics with practical applications in infectious disease diagnostics and causal inference frameworks. Her academic credentials include: PhD in Statistics, University of Rochester MA in Statistics, University of Rochester BS in Mathematics, Southwest Normal University, China Dr. He's research focuses on mixture population modeling, causal inference, longitudinal data analysis, and ROC analysis, with significant applications in tuberculosis diagnostics and molecular epidemiology. She develops novel statistical approaches for social media data analysis, drinking outcome modeling, and zero-modified datasets, emphasizing methodological rigor in public health contexts. Her textbook Applied Categorical and Count Data Analysis and edited volume Statistical Causal Inferences and Their Applications in Public Health Research establish her as a leading methodological authority. Recent publications (2023-2025) demonstrate a concentrated focus on CRISPR-based diagnostic technologies and next-generation sequencing for tuberculosis detection, with strong emphasis on point-of-care applications, diagnostic accuracy validation, and low-resource setting adaptations. These works integrate biostatistical innovation with molecular diagnostics to address critical gaps in infectious disease control. Her scientific recognition includes: Teaching Excellent Award (2020) Dr. He directs the Methodology/Biostatistics Unit at Tulane University Translational Science Institute (TUTSI) and serves as Principal Investigator for an NIH R01 grant Moving beyond description: statistical and causal inference for social media data , alongside multiple pilot studies and foundation-funded projects. She has contributed biostatistical expertise to dozens of NIH-funded investigations, particularly in tuberculosis and infectious disease research. As Co-director of TUTSI's Clinical Research Core and Statistical Deputy Editor for the American Journal of Public Health , she leads institutional research infrastructure while advancing methodological standards in public health science.

Julie AhringerView profile

Professor

• Chromatin Regulation
• Epigenetics
• Genome Organization
• +3 more

Julie Ahringer is Professor of Genetics and Genomics at the University of Cambridge and Director of the Wellcome Trust/Cancer Research UK Gurdon Institute. She leads a research group investigating chromatin structure and gene regulation using C. elegans as a model system. Her work integrates genomics, super-resolution microscopy, and computational approaches to understand epigenetic controls in development and disease. She holds fellowships from the Royal Society (FRS) and Academy of Medical Sciences (FMedSci). Research Focus: Her laboratory studies chromatin regulation mechanisms including heterochromatin formation, Polycomb domain function, genome architecture, and enhancer/promoter interactions. Key approaches include single-cell multiomics, high-throughput genomics, and super-resolution microscopy to analyze developmental trajectories. Research areas span: H3K27me3 domain formation and Polycomb repression Constitutive heterochromatin organization Regulatory element characterization 3D genome architecture via ARC-C technology Single-cell resolution developmental mapping Awards & Honors: Fellow of the Royal Society (FRS) Fellow of the Academy of Medical Sciences (FMedSci) Wellcome Senior Research Fellowship Academic Leadership: She mentors PhD students and postdoctoral researchers, with funding from Wellcome, MRC, and CRUK. Her lab develops open-source bioinformatics tools (VplotR, periodicDNA) and maintains the genome-wide C. elegans RNAi feeding library. Lab & Collaborations: The Ahringer Lab is based at the Gurdon Institute and collaborates widely on chromatin dynamics, nuclear organization, and developmental genomics projects across model organisms.

Lei TianView profile

Associate Professor

• Computational imaging and sensing
• Computational microscopy
• Imaging in scattering media
• +5 more

Lei Tian is an Associate Professor in the Department of Electrical and Computer Engineering and the Department of Biomedical Engineering at Boston University's College of Engineering. He leads the Computational Imaging Systems Lab and maintains affiliations with the Neurophotonics Center, Photonics Center, Center for Information & System Engineering, Rafik B. Hariri Institute for Computing, and Nanotechnology Innovation Center. His educational background includes: PhD, Massachusetts Institute of Technology, 2013 MS, Massachusetts Institute of Technology, 2010 Professor Tian's research integrates optics and computation to overcome physical limitations in imaging systems. His work spans computational imaging and sensing, computational microscopy, imaging in scattering media, phase retrieval, and neurophotonics. He develops next-generation imaging systems with applications in biomedical microscopy, neuroscience, semiconductor metrology, and advanced vision applications, emphasizing the joint design of optical components and computational algorithms. His publication record shows a strong progression from fundamental computational imaging techniques to practical applications, with increasing integration of deep learning approaches to solve challenging imaging problems in scattering media and neural environments. His work consistently bridges theoretical advances with real-world applications. Professor Tian has received numerous prestigious awards: Boston University Provost's Scholar-Teacher of the Year Award (2025) Optica Fellow (2025) Early Career Excellence in Research, BU College of Engineering (2021) NSF CAREER Award (2019) Dean's Catalyst Award (2018) The Fumio Okano Best 3D Paper Prize (2018) As an advisor, he has successfully mentored at least 10 PhD students to completion as of mid-2025, with recent graduates including Jeffrey Alido, Jiabei Zhu, Chang Liu, Hao Wang, and Joseph Greene. His research is supported by substantial funding including a $2 million NIH grant for the Computational Miniature Mesoscope (CM2), a $1.75M grant from NIBIB for cancer cell metabolism research, and funding from the Chan Zuckerberg Initiative. His Computational Imaging Systems Lab pioneers innovative imaging techniques that synergistically combine optical hardware with computational algorithms, making significant contributions to computational microscopy, intensity diffraction tomography, neural imaging systems, and deep learning applications in optical imaging for both biomedical and industrial applications.

Ben Z. StangerView profile

Professor

• Pancreatic Cancer
• Cellular Plasticity
• Tumor Immunology
• +3 more

Ben Z. Stanger, M.D., Ph.D. is the Hanna Wise Professor in Cancer Research at the University of Pennsylvania's Perelman School of Medicine, with appointments in the Department of Medicine and Cell and Developmental Biology. He serves as Director of the Penn Pancreatic Cancer Research Center (PCRC) and is an active member of the Abramson Cancer Center, Institute for Diabetes, Obesity and Metabolism, Institute for Medicine and Engineering, and Institute for Regenerative Medicine. His laboratory is housed in the Biomedical Research Building II/III on the Penn campus in Philadelphia. Education: SB (Life Sciences) from Massachusetts Institute of Technology, 1988 MD and PhD (Genetics) from Harvard Medical School, 1997 Dr. Stanger's research focuses on pancreatic ductal adenocarcinoma (PDAC), which is poised to become the second leading cause of cancer death in the United States. His laboratory investigates how pancreatic tumors metastasize early in disease progression and identifies therapeutic vulnerabilities through studies of the tumor microenvironment, metabolism, cellular plasticity, and metastasis biology. His team employs genetically engineered mouse models that recapitulate human disease features, functional genomics, epigenetic analyses, and advanced in vitro culture systems. Analysis of Dr. Stanger's recent publications (2019-2024) reveals a consistent focus on pancreatic cancer biology with increasing emphasis on tumor immunology and therapeutic resistance mechanisms. His research has evolved from fundamental studies of tumor-stroma interactions toward more translational investigations of KRAS inhibition, immune microenvironment regulation, and cellular reprogramming in cancer. Recent work demonstrates how tumor plasticity drives resistance to immunotherapy and how metabolic adaptations allow cancer cells to survive nutrient-deprived conditions. Dr. Stanger maintains an active laboratory with diverse personnel including postdoctoral researchers, graduate students, research specialists, and administrative support. His lab has published in high-impact journals including Nature Communications, Cancer Discovery, Cancer Research, and Science. In addition to his research, Dr. Stanger has authored the book "From One Cell: A Journey into Life's Origins and the Future of Medicine" which explores embryonic development through the lens of scientific history. Research Team: Principal Investigator: Ben Stanger, MD, PhD Research Specialists: Chenghua Yang (Lab Manager), Lily Watson (Assistant Lab Manager) Research Coordinator: Sean O'Connor Postdoctoral Researchers: Austin Good, Cole Edwards, Feiyan Mo, Minh Than Graduate/Post-Graduate Students: Erin Hollander, Benjamin Kahn, Jayne McDevitt, Margo Orlen, William Sullivan, Jane Xie Undergraduate Researcher: Shreya Nair Executive Administrator: Fran Tucker

Filipe PereiraView profile

Professor

• Cellular Reprogramming
• Hematopoiesis
• Immunology
• +5 more

Filipe Pereira is a Professor and Senior Lecturer at Lund University's Faculty of Medicine, where he holds a Wallenberg Molecular Medicine Fellowship and leads the Cell Reprogramming in Hematopoiesis and Immunity research team within the Division of Molecular Medicine and Gene Therapy. His work contributes to UN Sustainable Development Goals related to health and well-being. Dr. Pereira's research focuses on understanding the molecular determinants of cell reprogramming and hematopoietic specification. His laboratory investigates how cellular identities are specified during development, with particular emphasis on Hematopoietic Stem Cells (HSCs) for their regenerative potential and Dendritic Cells (DCs) as key orchestrators of immunity. The team explores experimental approaches to cell reprogramming including nuclear transfer, cell fusion, and transcription factor expression to develop new therapies for immune and blood diseases. Analysis of Dr. Pereira's 98 research outputs reveals a strong focus on cellular reprogramming techniques for immunotherapy applications, particularly in cancer treatment. His work spans molecular biology, immunology, and stem cell research, with significant contributions to understanding transcription factor networks that control cell fate decisions. The research has practical applications in regenerative medicine and cancer immunotherapy, with several publications in high-impact journals including Nature Communications and Science Immunology. Scientific Recognition: Imperial College Emerging Alumni Leader Award (2025) ERC Proof of Concept grant (2024) Pfizer-Portugal award in basic research (2024) ERC Proof of Concept Grant (2023) Eric K. Fernströms Prize to young particularly promising researchers (2023) Dr. Pereira actively supervises graduate students and postdoctoral researchers, with 12 PhD students and 8 postdocs under his mentorship. He leads multiple research projects including 'In Vivo Dendritic Cell Reprogramming Immunotherapy' and 'Functional chemical reprogramming of cancer cells to induce antitumor immunity,' funded by organizations including the European Commission and Cancer Research Institute. His laboratory has developed innovative approaches to reprogram somatic cells into desired hematopoietic cell types, with significant implications for therapeutic applications. The Cell Reprogramming in Hematopoiesis and Immunity team collaborates extensively across international boundaries, with research outputs picked up by numerous news outlets and referenced in patents and Wikipedia pages, demonstrating the broad impact of their work in the scientific community and beyond.

Aly KarsanView profile

Professor

• Leukemia
• Hematopoiesis
• Genomics
• +8 more

Aly Karsan is a Professor in the Department of Pathology and Laboratory Medicine at the University of British Columbia (UBC) and a Distinguished Scientist at Canada’s Michael Smith Genome Sciences Centre at BC Cancer. His research focuses on the molecular basis of myeloid leukemias, aging-related cancer resistance, and clinical genomics innovation. Affiliations: Faculty of Medicine (UBC), School of Biomedical Engineering (UBC), BC Cancer Research Institute, Centre for Blood Research (UBC) Clinical leadership: Established first clinically-accredited Next-Generation Sequencing lab in Canada Research Interests Dr. Karsan investigates: Genomic and epigenomic aberrations in aging-related leukemia Role of noncoding RNAs and innate immune signaling in blood cancers Embryonic blood stem cell emergence via Sash1 signaling Clonal interactions in acute myeloid leukemia (AML) Mechanisms of lenalidomide resistance in myelodysplastic syndromes Scientific Contributions Recent publications demonstrate expertise in: NGS technology validation Genetic barcoding systems TGFβ signaling in hematopoiesis Bayesian network diagnostics Awards & Recognition Tier 1 Canada Research Chair in Blood Cancers John Auston BC Cancer Foundation Clinical Scientist Award Health Employers Association of BC Gold Apple Award for Innovation Multiple CIHR Clinician-Scientist and MSFHR Scholar awards Labs & Collaborations Leads the Karsan Lab at BC Cancer Research Institute and coordinates a Terry Fox Research Institute Program Project with six principal investigators.

Wendy RobinsonView profile

Professor

• Medical Genetics
• Epigenetics
• Fetal Development
• +4 more

Wendy P. Robinson is a Professor in the Department of Medical Genetics at the University of British Columbia Faculty of Medicine , and a Senior Scientist at the BC Children’s Hospital Research Institute . She holds the CIHR Sex and Gender Science Chair . Research Interests: Genetics and epigenetics of early human development, placental function in pregnancy complications (fetal growth restriction, preterm birth), DNA methylation, non-coding RNA, sex differences, and polymorphisms. Her lab employs genomic and bioinformatic tools to study placental health and its impact on newborn outcomes. Recent Publications (2025-2024) focus on X-chromosome inactivation patterns in placenta, cell-type specific DNA methylation, maternal socioeconomic effects on placental epigenetics, and modeling placental development with organoids. Key themes include sex-specific epigenetic regulation , maternal-fetal interactions , and human placental methylome . Awards: UBC Faculty of Medicine Distinguished Achievement Award (2018), with trainees receiving the James Miller Memorial Prize and Mary-Jane Carroll Trainee Award. Students & Collaborations: Supervised PhD/MSc students include Li Qing Wang, Icíar Fernández Boyano, Giulia Del Gobbo, Victor Yuan, and Magda Price. Collaborators span the Alex Beristain Lab and University of Toronto institutions. Laboratory Activities: Regular team-building events like mountain hikes, climbing outings, and kayaking trips, alongside providing open access to epigenetic tools (e.g., Bisearch, SeqDoc) for the research community.